apply.tbin {corkscrew} | R Documentation |
Extrapolate t-test based binning to a new data
Description
Extrapolates the binning of categorical variables to the new datasets.
Usage
apply.tbin(idv, train.output, test)
Arguments
idv |
Predictor variables in the dataframe which are categorical and need to be binned. |
train.output |
The output object of the tbin function. |
test |
A new data set on which binning has to be extrapolated. |
Details
This function performs binning on the new dataset based on the output object from the tbin function.
Value
Returns a dataframe which contains the extrapolated variables of the output object from tbin function appended to the new dataset.
Warning
New level error is thrown if the new dataset contains new levels other than what is present in the old dataset.
Author(s)
Mohan Manivannan
See Also
tbin
, ctoc
, apply.ctoc
.
Examples
train = as.data.frame(cbind(runif(1000, 10, 1000),sample(1:40, 1000,TRUE)))
colnames(train) = c("response","state")
train$state = as.factor(train$state)
train.output = tbin(dv = "response",idv = c("state"),train,25,TRUE)
# extrapolating the tbin function to a new dataset using apply.tbin
test = as.data.frame(sample(1:40, 100,TRUE))
colnames(test) = c("state")
test$state = as.factor(test$state)
test.output = apply.tbin(idv = c("state"), train.output, test)
[Package corkscrew version 1.1 Index]